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TECHNOLOGICAL COMPETENCE AND LEARNING ENGAGEMENT ON
MATHEMATICAL FLUENCY OF STUDENTS: A CAUSAL MODEL
OSCAR JAYSON ARIGO JR
MASTER THESIS SUBMITTED TO THE FACULTY OF THE DEPARTMENT
OF MATHEMATICS EDUCATION, COLLEGE OF EDUCATION,
CENTRAL MINDANAO UNIVERSITY, IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE
MASTER OF SCIENCE IN MATHEMATICS EDUCATION
DECEMBER 2021
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Republic of the Philippines
CENTRAL MINDANAO UNIVERSITY
University Town, Musuan, Bukidnon
College of Education
Department of Science Education
APPROVAL SHEET
This masters thesis attached hereto entitled, “TECHNOLOGICAL
COMPETENCE AND LEARNING ENGAGEMENT ON MATHEMATICAL
FLUENCY OF STUDENTS: A CAUSAL MODEL” (Research No.G-305),
prepared and submitted by OSCAR JAYSON ARIGO JR, in partial fulfillment of
the requirements for the degree Master of Science in Mathematics Education, is
hereby accepted.
RAUL C. ORONGAN, PhD
Chair, Thesis Advisory Committee
Date: _______________
________________________
Examiner
Date: _______________
DENIS A. TAN, PhD
Member, Thesis Advisory Committee
Date: _______________
________________________
Examiner
Date: _______________
CHERLY C. CORDOVA, PhD
Member, Thesis Advisory Committee
Date: _______________
Recommending Approval:
EHLRICH RAY J. MAGDAY
Department Chairperson
_____________
Date
RAUL C. ORONGAN, PhD
College Research Coordinator
_____________
Date
Approved:
GLADYS S. ESCARLOS, PhD
College Dean
______________
Date
Noted:
JUPITER V. CASAS, PhD
Director for Research
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______________
Date
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TABLE OF CONTENTS
PAGE
INTRODUCTION
Background of the Study
Statement of the Problem
Objectives of the Study
Significance of the Study
Scope and Delimitations of the Study
Definition of Terms
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4
5
6
7
7
THEORETICAL FRAMEWORK
Review of Related Studies and Literature
Conceptual Framework
Hypothesized Causal Model 1
Hypothesized Causal Model 2
Hypothesized Causal Model 3
Hypotheses of the study
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23
26
27
28
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RESEARCH METHODOLOGY
Research Design
Locale of the Study
Participants of the Study
Sampling Procedure
Research Instrument
Data Gathering Procedure
Statistical Analysis
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30
32
32
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35
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PRESENTATION, ANALYSIS AND INTERPRETATION
Students’ performance in Mathematical fluency
Technological Competence
Learning Engagement
Relationship Between Independent variables
and Mathematical Fluency of Students
Regression Analysis of Performance to Technological
Competence and Learning Engagement
Causal Model of Mathematical Fluency Performance
Causal Model 1
Causal Model 2
Causal Model 3
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
Summary
Conclusions
Recommendations
Bibliography
Appendices
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LIST OF TABLES
TABLE
1
PAGE
Variables used, its code and nature
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and how each was measured in the study
2
Distribution of the participants
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3
Level of students’ mathematical fluency in Algebra
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4
Level of students’ mathematical fluency in Geometry
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5
Level of students’ mathematical fluency in Trigonometry
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6
Overall students’ Performance in Mathematical Fluency
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7
Uses of Technology in education
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Emotional effect of Technology to Students
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Students’ Proficiency
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Students’ cognitive engagement
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11
Students Behavioral engagement
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12
Students’ Emotional Engagement
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13
Students Social Engagement
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14
Correlation Analysis between Independent Variables
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and Mathematical Fluency Performance
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Regression Analysis between Independent Variables
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and Mathematical Fluency Performance
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Direct effect of Independent variables of Causal Model 1
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On Mathematical Fluency Performance
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Standard of Fit Indices for Causal Model 1 and Standard Value
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Direct effect and Indirect effect of Independent variables
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LIST OF TABLES
TABLE
PAGE
of Causal Model 2 on Mathematical Fluency Performance
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Standard of Fit Indices for Model 2 and Standard Value
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20
Direct effect and Indirect effect of Independent variables
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of Causal Model 3 on Mathematical Fluency Performance
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Standard of Fit Indices for Model 3 and Standard Value
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22
Summary of Standard of Fit Indices
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LIST OF FIGURES
FIGURE
PAGE
1. Hypothesized Causal Model 1
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2. Hypothesized Causal Model 2
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3. Hypothesized Causal Model 3
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4. Map of the Locale of the study
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5. Path Model 1 Showing the Direct Relationship of
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Technological Competence and Learning Engagement
on Mathematical Fluency Performance
6. Path Model 2 Showing the Direct Relationship of
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Technological Competence and Learning Engagement
on Mathematical Fluency Performance
7. Path Model 3 Showing the Direct Relationship of
Technological Competence and Learning Engagement
on Mathematical Fluency Performance
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LIST OF APPENDICES
APPENDIX
A. Technological Competence Questionnaire
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B. Student’s Learning Engagement Questionnaire
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C. Mathematics Fluency test for Students
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D. Table of Specification
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E. Approved letter of the Division of Bukidnon in
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Conducting the study
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PAGE
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ABSTRACT
ARIGO, OSCAR JR. JAYSON. Central Mindanao University, Musuan,
Bukidnon, December 2021. Technological Competence and Learning
Engagement on Mathematical Fluency of Student: A Causal Model
Adviser: Dr. Raul C. Orongan
This study aimed to investigate the technological competence and
learning engagement on mathematical fluency of Grade 10 students of the
three secondary schools that represent the three districts of Maramag.
Specifically, it aimed to: 1.) describe the level of mathematical fluency of
students in terms of Algebra, Geometry and Trigonometry; 2) determine the
level of technological competence towards learning mathematics of students
in terms of uses of technology, emotional effect and proficiency; 3.) ascertain
the level of student’s learning engagement in terms of cognitive, behavioral,
emotional and social engagement; 4.) assess the relationship among
mathematical fluency, technological competence and learning engagement of
grade 10 students; 5.) identify the variables singly or in combination best
predict mathematical fluency of students in the new normal; and 6.) develop
the causal model best fits on mathematical fluency of grade 9 students in the
new normal. An academic assessment and non-academic assessment was
used in the study. The research utilized items adapted from DepEd-Bukidnon
for assessing the mathematical fluency of students. Non-academic
assessment such as technological competence and engagement survey
instruments were used. Descriptive statistics, Pearson correlation, regression
and path analysis were used in the study.
The findings of the study revealed that level of students’ mathematical
fluency is poor and among the three components of mathematical fluency test,
students are extremely poor in trigonometry. In Technological competence of
students, uses of technology have a positive result and learning engagement
of students in Mathematics during pandemic is moderately positive. It is
revealed that there is a significant relationship between students’ mathematical
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fluency and their technological competence in terms of uses of technology,
emotional effect and proficiency. However, there is no significant relationship
between learning engagement towards mathematical fluency of students. The
variables that best predicts mathematical fluency performance of students are
uses of technology and cognitive engagement. The causal model that best fit
on mathematical fluency of students is anchored on uses of technology. This
model is supported with their technological competence in terms of proficiency,
and emotional effect and learning engagement in terms of cognitive, social and
emotional engagement. The more students engage themselves in technology
in the new normal, the better performance in Mathematics is achieved.
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